Items related to Advances in Machine Learning and Data Analysis
Synopsis
1 2D/3D Image Data Analysis for Object Tracking and Classification; Seyed Eghbal Ghobadi, Omar Edmond Loepprich, Oliver Lottner, Klaus Hartmann, Wolfgang Weihs, Otmar Loffeld. 2 Robot Competence Development by Constructive Learning ; Q. Meng, M.H. Lee, C.J. Hinde. 3 Using DigitalWatermarking for Securing Next Generation Media Broadcasts; Dominik Birk, Seán Gaines. 4 A Reduced-Dimension ProcessorModel; Azam Beg. 5 Hybrid Machine Learning Model for Continuous Microarray Time Series; S.-I. Ao. 6 An Asymptotic Method to a Financial Optimization Problem; Dejun Xie, David Edwards, Giberto Schleiniger. 7 Analytical Design of Robust Multi-loop PI Controller for Multi-time Delay Processes; Truong Nguyen Luan Vu, Moonyong Lee. 8 Automatic and Semi-automaticMethods for the Detection of Quasars in Sky Surveys; S.-I. Ao. 9 Improving Low-Cost Sail Simulator Results by Artificial Neural Networks Models; V. Díaz Casás, P. Porca Belío, F. López Peña, R.J. Duro. 10 Rough Set Approaches to Unsupervised Neural Network Based Pattern Classifier; Ashwin Kothari, Avinash Keskar. 11 A New Robust Combined Method for Auto Exposure and Auto White-Balance; Quoc Kien Vuong, Se-Hwan Yun, Suki Kim. 12 A Mathematical Analysis Around Capacitive Characteristics of the Current of CSCT: Optimum Utilization of Capacitors of Harmonic Filters; Mohammad Golkhah, Mohammad Tavakoli Bina. 13 Harmonic Analysis and Optimum Allocation of Filters in CSCT; Mohammad Golkhah, Mohammad Tavakoli Bina. 14 Digital Pen and Paper Technology as a Means of Classroom Administration Relief; Jan Broer, Tim Wendisch, Nina Willms. 15 A Conceptual Model for a Network-Based Assessment Security System; Nathan Percival, Jennifer Percival, Clemens Martin. 16 IncorrectWeighting of Absolute Performance in Self-Assessment; Scott A. Jeffrey, Brian Cozzarin.
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Review
From the reviews: “This is a collection of papers from a large international conference on advances in machine learning and data analysis … . Readers who work with digital systems … would benefit most from this book. … Each chapter has … a bibliography that helps readers find further references, when needed. … the topics covered in this book should be of great interest to researchers and practitioners who want to apply machine learning technology and data analysis tools to problems in general electrical engineering areas … .” (Xiannong Meng, ACM Computing Reviews, March, 2010)
"About this title" may belong to another edition of this title.
- PublisherSpringer
- Publication date2010
- ISBN 10 9048131782
- ISBN 13 9789048131785
- BindingPaperback
- LanguageEnglish
- Number of pages248
- EditorAmouzegar Mahyar
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